GitHub

ChaseWiederstein/Schur-Algorithms-for-Cholesky-Factorization-of-Displacement-Matrices

This project implements and validates the Schur algorithm for computing the Cholesky factor of symmetric positive definite (SPD) matrices and Toeplitz matrices with displacement ranks 2 and 4. The ...
IEEE

Linear statistical models for stationary sequences and related algorithms for Cholesky factorization of Toeplitz matrices

Abstract: We review the Levinson-Durbin recursions for computing the Cholesky factors of the inverse of a Toeplitz correlation matrix R, and the Schur recursions for computing the Cholesky factors of ...
Visual Studio Magazine

Kernel Ridge Regression with Cholesky Inverse Training Using JavaScript

Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...
IEEE

Comprehensive Study on Zeroing Neural Network With High-Order Evolutionary Formula, Nonlinear Functions, and Variable Parameter for Time-Changing Matrix Cholesky Decomposition

Abstract: In this article, a low-order zeroing neural network (LZNN), a high-order ZNN (HZNN), and a variable-parameter ZNN (VZNN) are designed and applied to the time-changing Cholesky decomposition ...
GitHub

Kallistina/linear-numerical-algebra

This course focuses on numerical methods in scientific computing, with a particular emphasis on linear algebra operations such as matrix decompositions, solving systems of equations, and eigenvalue ...